arm_compute v17.09
Change-Id: I4bf8f4e6e5f84ce0d5b6f5ba570d276879f42a81
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<title>Compute Library: examples/neon_convolution.cpp File Reference</title>
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@@ -120,9 +118,9 @@
<div class="title">neon_convolution.cpp File Reference</div> </div>
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<div class="contents">
-<div class="textblock"><code>#include "<a class="el" href="_n_e_functions_8h_source.xhtml">arm_compute/runtime/NEON/NEFunctions.h</a>"</code><br />
-<code>#include "<a class="el" href="arm__compute_2core_2_types_8h_source.xhtml">arm_compute/core/Types.h</a>"</code><br />
-<code>#include "<a class="el" href="utils_2_utils_8h_source.xhtml">utils/Utils.h</a>"</code><br />
+<div class="textblock"><code>#include "<a class="el" href="_n_e_functions_8h_source.xhtml">arm_compute/runtime/NEON/NEFunctions.h</a>"</code><br/>
+<code>#include "<a class="el" href="arm__compute_2core_2_types_8h_source.xhtml">arm_compute/core/Types.h</a>"</code><br/>
+<code>#include "<a class="el" href="utils_2_utils_8h_source.xhtml">utils/Utils.h</a>"</code><br/>
</div>
<p><a href="neon__convolution_8cpp_source.xhtml">Go to the source code of this file.</a></p>
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@@ -131,16 +129,16 @@
<tr class="memitem:ac741ff15d9366f7bf55dc470e87144d3"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="neon__convolution_8cpp.xhtml#ac741ff15d9366f7bf55dc470e87144d3">main_neon_convolution</a> (int argc, const char **argv)</td></tr>
<tr class="separator:ac741ff15d9366f7bf55dc470e87144d3"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a217dbf8b442f20279ea00b898af96f52"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="neon__convolution_8cpp.xhtml#a217dbf8b442f20279ea00b898af96f52">main</a> (int argc, const char **argv)</td></tr>
-<tr class="memdesc:a217dbf8b442f20279ea00b898af96f52"><td class="mdescLeft"> </td><td class="mdescRight">Main program for convolution test. <a href="#a217dbf8b442f20279ea00b898af96f52">More...</a><br /></td></tr>
+<tr class="memdesc:a217dbf8b442f20279ea00b898af96f52"><td class="mdescLeft"> </td><td class="mdescRight">Main program for convolution test. <a href="#a217dbf8b442f20279ea00b898af96f52">More...</a><br/></td></tr>
<tr class="separator:a217dbf8b442f20279ea00b898af96f52"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="var-members"></a>
Variables</h2></td></tr>
<tr class="memitem:a741ba5321da40184f8653e0a50ace070"><td class="memItemLeft" align="right" valign="top">const int16_t </td><td class="memItemRight" valign="bottom"><a class="el" href="neon__convolution_8cpp.xhtml#a741ba5321da40184f8653e0a50ace070">gaussian3x3</a> []</td></tr>
-<tr class="memdesc:a741ba5321da40184f8653e0a50ace070"><td class="mdescLeft"> </td><td class="mdescRight">Gaussian 3x3 matrix. <a href="#a741ba5321da40184f8653e0a50ace070">More...</a><br /></td></tr>
+<tr class="memdesc:a741ba5321da40184f8653e0a50ace070"><td class="mdescLeft"> </td><td class="mdescRight">Gaussian 3x3 matrix. <a href="#a741ba5321da40184f8653e0a50ace070">More...</a><br/></td></tr>
<tr class="separator:a741ba5321da40184f8653e0a50ace070"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a565013cf7e49a591bacd548571951f94"><td class="memItemLeft" align="right" valign="top">const int16_t </td><td class="memItemRight" valign="bottom"><a class="el" href="neon__convolution_8cpp.xhtml#a565013cf7e49a591bacd548571951f94">gaussian5x5</a> []</td></tr>
-<tr class="memdesc:a565013cf7e49a591bacd548571951f94"><td class="mdescLeft"> </td><td class="mdescRight">Gaussian 5x5 matrix. <a href="#a565013cf7e49a591bacd548571951f94">More...</a><br /></td></tr>
+<tr class="memdesc:a565013cf7e49a591bacd548571951f94"><td class="mdescLeft"> </td><td class="mdescRight">Gaussian 5x5 matrix. <a href="#a565013cf7e49a591bacd548571951f94">More...</a><br/></td></tr>
<tr class="separator:a565013cf7e49a591bacd548571951f94"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<h2 class="groupheader">Function Documentation</h2>
@@ -180,7 +178,10 @@
<p>Definition at line <a class="el" href="neon__convolution_8cpp_source.xhtml#l00114">114</a> of file <a class="el" href="neon__convolution_8cpp_source.xhtml">neon_convolution.cpp</a>.</p>
<p>References <a class="el" href="neon__convolution_8cpp_source.xhtml#l00052">main_neon_convolution()</a>, and <a class="el" href="utils_2_utils_8cpp_source.xhtml#l00069">arm_compute::utils::run_example()</a>.</p>
-<div class="fragment"><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> {</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1utils.xhtml#a4c9395db2c8b8d0c336656a7b58fca3e">utils::run_example</a>(argc, argv, <a class="code" href="neon__convolution_8cpp.xhtml#ac741ff15d9366f7bf55dc470e87144d3">main_neon_convolution</a>);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> }</div><div class="ttc" id="neon__convolution_8cpp_xhtml_ac741ff15d9366f7bf55dc470e87144d3"><div class="ttname"><a href="neon__convolution_8cpp.xhtml#ac741ff15d9366f7bf55dc470e87144d3">main_neon_convolution</a></div><div class="ttdeci">void main_neon_convolution(int argc, const char **argv)</div><div class="ttdef"><b>Definition:</b> <a href="neon__convolution_8cpp_source.xhtml#l00052">neon_convolution.cpp:52</a></div></div>
+<div class="fragment"><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> {</div>
+<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1utils.xhtml#a4c9395db2c8b8d0c336656a7b58fca3e">utils::run_example</a>(argc, argv, <a class="code" href="neon__convolution_8cpp.xhtml#ac741ff15d9366f7bf55dc470e87144d3">main_neon_convolution</a>);</div>
+<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> }</div>
+<div class="ttc" id="neon__convolution_8cpp_xhtml_ac741ff15d9366f7bf55dc470e87144d3"><div class="ttname"><a href="neon__convolution_8cpp.xhtml#ac741ff15d9366f7bf55dc470e87144d3">main_neon_convolution</a></div><div class="ttdeci">void main_neon_convolution(int argc, const char **argv)</div><div class="ttdef"><b>Definition:</b> <a href="neon__convolution_8cpp_source.xhtml#l00052">neon_convolution.cpp:52</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1utils_xhtml_a4c9395db2c8b8d0c336656a7b58fca3e"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml#a4c9395db2c8b8d0c336656a7b58fca3e">arm_compute::utils::run_example</a></div><div class="ttdeci">int run_example(int argc, const char **argv, example &func)</div><div class="ttdoc">Run an example and handle the potential exceptions it throws. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8cpp_source.xhtml#l00069">Utils.cpp:69</a></div></div>
</div><!-- fragment -->
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@@ -213,25 +214,78 @@
<p>Definition at line <a class="el" href="neon__convolution_8cpp_source.xhtml#l00052">52</a> of file <a class="el" href="neon__convolution_8cpp_source.xhtml">neon_convolution.cpp</a>.</p>
-<p>References <a class="el" href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">NEConvolution3x3::configure()</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">NEConvolutionSquare< matrix_size >::configure()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00142">PPMLoader::fill_image()</a>, <a class="el" href="neon__convolution_8cpp_source.xhtml#l00034">gaussian3x3</a>, <a class="el" href="neon__convolution_8cpp_source.xhtml#l00043">gaussian5x5</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00125">PPMLoader::init_image()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00114">PPMLoader::is_open()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00094">PPMLoader::open()</a>, <a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml#ab5fd6e96c07aaaed2747c7e16ed5951e">INESimpleFunction::run()</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb">NEConvolutionSquare< matrix_size >::run()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00245">arm_compute::utils::save_to_ppm()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>, and <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">arm_compute::UNDEFINED</a>.</p>
+<p>References <a class="el" href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">NEConvolution3x3::configure()</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">NEConvolutionSquare< matrix_size >::configure()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00187">PPMLoader::fill_image()</a>, <a class="el" href="neon__convolution_8cpp_source.xhtml#l00034">gaussian3x3</a>, <a class="el" href="neon__convolution_8cpp_source.xhtml#l00043">gaussian5x5</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00170">PPMLoader::init_image()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00159">PPMLoader::is_open()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00139">PPMLoader::open()</a>, <a class="el" href="classarm__compute_1_1_i_n_e_simple_function.xhtml#ab5fd6e96c07aaaed2747c7e16ed5951e">INESimpleFunction::run()</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb">NEConvolutionSquare< matrix_size >::run()</a>, <a class="el" href="utils_2_utils_8h_source.xhtml#l00281">arm_compute::utils::save_to_ppm()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>, and <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">arm_compute::UNDEFINED</a>.</p>
<p>Referenced by <a class="el" href="neon__convolution_8cpp_source.xhtml#l00114">main()</a>.</p>
-<div class="fragment"><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml">PPMLoader</a> ppm;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="struct_image.xhtml">Image</a> src, tmp, dst;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">if</span>(argc < 2)</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Print help</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  std::cout << <span class="stringliteral">"Usage: ./build/neon_convolution [input_image.ppm]\n\n"</span>;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::cout << <span class="stringliteral">"No input_image provided, creating a dummy 640x480 image\n"</span>;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Initialize just the dimensions and format of your buffers:</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  src.allocator()->init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(640, 480, Format::U8));</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  }</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a36e58f3e64f3851ebac7a9556b4704ed">open</a>(argv[1]);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="comment">// Initialize just the dimensions and format of your buffers:</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a69f2a0e263d4f77d1e166de9cd2746f7">init_image</a>(src, Format::U8);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  }</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Initialize just the dimensions and format of the temporary and destination images:</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  tmp.allocator()->init(*src.info());</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  dst.allocator()->init(*src.info());</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="classarm__compute_1_1_n_e_convolution3x3.xhtml">NEConvolution3x3</a> conv3x3;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml">NEConvolution5x5</a> conv5x5;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">// Apply a Gaussian 3x3 filter to the source image followed by a Gaussian 5x5:</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="comment">// The function will automatically update the padding information inside input and output to match its requirements</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  conv3x3.<a class="code" href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">configure</a>(&src, &tmp, <a class="code" href="neon__convolution_8cpp.xhtml#a741ba5321da40184f8653e0a50ace070">gaussian3x3</a>, 0 <span class="comment">/* Let arm_compute calculate the scale */</span>, BorderMode::UNDEFINED);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  conv5x5.<a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">configure</a>(&tmp, &dst, <a class="code" href="neon__convolution_8cpp.xhtml#a565013cf7e49a591bacd548571951f94">gaussian5x5</a>, 0 <span class="comment">/* Let arm_compute calculate the scale */</span>, BorderMode::UNDEFINED);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="comment">// Now that the padding requirements are known we can allocate the images:</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  src.allocator()->allocate();</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  tmp.allocator()->allocate();</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  dst.allocator()->allocate();</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="comment">// Fill the input image with the content of the PPM image if a filename was provided:</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">if</span>(ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a2f57f54d8c03b615bb31eee091d8a88a">is_open</a>())</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a1672610b872bef30d0dc2333a0ffc402">fill_image</a>(src);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  }</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">//Execute the functions:</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  conv3x3.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function.xhtml#ab5fd6e96c07aaaed2747c7e16ed5951e">run</a>();</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  conv5x5.<a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="comment">// Save the result to file:</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">if</span>(ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a2f57f54d8c03b615bb31eee091d8a88a">is_open</a>())</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keyword">const</span> std::string output_filename = std::string(argv[1]) + <span class="stringliteral">"_out.ppm"</span>;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">save_to_ppm</a>(dst, output_filename);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> }</div><div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a1672610b872bef30d0dc2333a0ffc402"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a1672610b872bef30d0dc2333a0ffc402">arm_compute::utils::PPMLoader::fill_image</a></div><div class="ttdeci">void fill_image(T &image)</div><div class="ttdoc">Fill an image with the content of the currently open PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00142">Utils.h:142</a></div></div>
-<div class="ttc" id="namespacearm__compute_1_1utils_xhtml_a301d0b7bfd70f73fc1924f4281938d08"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">arm_compute::utils::save_to_ppm</a></div><div class="ttdeci">void save_to_ppm(T &tensor, const std::string &ppm_filename)</div><div class="ttdoc">Template helper function to save a tensor image to a PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00245">Utils.h:245</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml_a58d050865536a28b56a92eeaf3ac478e"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">arm_compute::NEConvolutionSquare::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function&#39;s source, destination, conv and border_mode. </div></div>
-<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a36e58f3e64f3851ebac7a9556b4704ed"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a36e58f3e64f3851ebac7a9556b4704ed">arm_compute::utils::PPMLoader::open</a></div><div class="ttdeci">void open(const std::string &ppm_filename)</div><div class="ttdoc">Open a PPM file and reads its metadata (Width, height) </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00094">Utils.h:94</a></div></div>
+<div class="fragment"><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> {</div>
+<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml">PPMLoader</a> ppm;</div>
+<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="struct_image.xhtml">Image</a> src, tmp, dst;</div>
+<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div>
+<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">if</span>(argc < 2)</div>
+<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  {</div>
+<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Print help</span></div>
+<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  std::cout << <span class="stringliteral">"Usage: ./build/neon_convolution [input_image.ppm]\n\n"</span>;</div>
+<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::cout << <span class="stringliteral">"No input_image provided, creating a dummy 640x480 image\n"</span>;</div>
+<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Initialize just the dimensions and format of your buffers:</span></div>
+<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  src.allocator()->init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(640, 480, Format::U8));</div>
+<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  }</div>
+<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">else</span></div>
+<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div>
+<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a36e58f3e64f3851ebac7a9556b4704ed">open</a>(argv[1]);</div>
+<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="comment">// Initialize just the dimensions and format of your buffers:</span></div>
+<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a69f2a0e263d4f77d1e166de9cd2746f7">init_image</a>(src, Format::U8);</div>
+<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  }</div>
+<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div>
+<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Initialize just the dimensions and format of the temporary and destination images:</span></div>
+<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  tmp.allocator()->init(*src.info());</div>
+<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  dst.allocator()->init(*src.info());</div>
+<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div>
+<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="classarm__compute_1_1_n_e_convolution3x3.xhtml">NEConvolution3x3</a> conv3x3;</div>
+<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml">NEConvolution5x5</a> conv5x5;</div>
+<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div>
+<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">// Apply a Gaussian 3x3 filter to the source image followed by a Gaussian 5x5:</span></div>
+<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="comment">// The function will automatically update the padding information inside input and output to match its requirements</span></div>
+<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  conv3x3.<a class="code" href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">configure</a>(&src, &tmp, <a class="code" href="neon__convolution_8cpp.xhtml#a741ba5321da40184f8653e0a50ace070">gaussian3x3</a>, 0 <span class="comment">/* Let arm_compute calculate the scale */</span>, BorderMode::UNDEFINED);</div>
+<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  conv5x5.<a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">configure</a>(&tmp, &dst, <a class="code" href="neon__convolution_8cpp.xhtml#a565013cf7e49a591bacd548571951f94">gaussian5x5</a>, 0 <span class="comment">/* Let arm_compute calculate the scale */</span>, BorderMode::UNDEFINED);</div>
+<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div>
+<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="comment">// Now that the padding requirements are known we can allocate the images:</span></div>
+<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  src.allocator()->allocate();</div>
+<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  tmp.allocator()->allocate();</div>
+<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  dst.allocator()->allocate();</div>
+<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div>
+<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="comment">// Fill the input image with the content of the PPM image if a filename was provided:</span></div>
+<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">if</span>(ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a2f57f54d8c03b615bb31eee091d8a88a">is_open</a>())</div>
+<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  {</div>
+<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a1672610b872bef30d0dc2333a0ffc402">fill_image</a>(src);</div>
+<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  }</div>
+<div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div>
+<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">//Execute the functions:</span></div>
+<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  conv3x3.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function.xhtml#ab5fd6e96c07aaaed2747c7e16ed5951e">run</a>();</div>
+<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  conv5x5.<a class="code" href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div>
+<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div>
+<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="comment">// Save the result to file:</span></div>
+<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">if</span>(ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a2f57f54d8c03b615bb31eee091d8a88a">is_open</a>())</div>
+<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  {</div>
+<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keyword">const</span> std::string output_filename = std::string(argv[1]) + <span class="stringliteral">"_out.ppm"</span>;</div>
+<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">save_to_ppm</a>(dst, output_filename);</div>
+<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div>
+<div class="line"><a name="l00107"></a><span class="lineno"> 107</span> }</div>
+<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a1672610b872bef30d0dc2333a0ffc402"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a1672610b872bef30d0dc2333a0ffc402">arm_compute::utils::PPMLoader::fill_image</a></div><div class="ttdeci">void fill_image(T &image)</div><div class="ttdoc">Fill an image with the content of the currently open PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00187">Utils.h:187</a></div></div>
+<div class="ttc" id="namespacearm__compute_1_1utils_xhtml_a301d0b7bfd70f73fc1924f4281938d08"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">arm_compute::utils::save_to_ppm</a></div><div class="ttdeci">void save_to_ppm(T &tensor, const std::string &ppm_filename)</div><div class="ttdoc">Template helper function to save a tensor image to a PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00281">Utils.h:281</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml_a58d050865536a28b56a92eeaf3ac478e"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml#a58d050865536a28b56a92eeaf3ac478e">arm_compute::NEConvolutionSquare::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function's source, destination, conv and border_mode. </div></div>
+<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a36e58f3e64f3851ebac7a9556b4704ed"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a36e58f3e64f3851ebac7a9556b4704ed">arm_compute::utils::PPMLoader::open</a></div><div class="ttdeci">void open(const std::string &ppm_filename)</div><div class="ttdoc">Open a PPM file and reads its metadata (Width, height) </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00139">Utils.h:139</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEConvolutionSquare::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function. </div></div>
-<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml">arm_compute::NEConvolutionSquare</a></div><div class="ttdoc">Basic function to execute convolution of size 5x5, 7x7, 9x9. </div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8h_source.xhtml#l00069">NEConvolution.h:69</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_n_e_convolution3x3_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution3x3.xhtml">arm_compute::NEConvolution3x3</a></div><div class="ttdoc">Basic function to execute convolution of size 3x3. </div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8h_source.xhtml#l00046">NEConvolution.h:46</a></div></div>
-<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a2f57f54d8c03b615bb31eee091d8a88a"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a2f57f54d8c03b615bb31eee091d8a88a">arm_compute::utils::PPMLoader::is_open</a></div><div class="ttdeci">bool is_open()</div><div class="ttdoc">Return true if a PPM file is currently open. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00114">Utils.h:114</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_n_e_convolution_square_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution_square.xhtml">arm_compute::NEConvolutionSquare</a></div><div class="ttdoc">Basic function to execute convolution of size 5x5, 7x7, 9x9. </div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8h_source.xhtml#l00072">NEConvolution.h:72</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_n_e_convolution3x3_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution3x3.xhtml">arm_compute::NEConvolution3x3</a></div><div class="ttdoc">Basic function to execute convolution of size 3x3. </div><div class="ttdef"><b>Definition:</b> <a href="_n_e_convolution_8h_source.xhtml#l00049">NEConvolution.h:49</a></div></div>
+<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a2f57f54d8c03b615bb31eee091d8a88a"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a2f57f54d8c03b615bb31eee091d8a88a">arm_compute::utils::PPMLoader::is_open</a></div><div class="ttdeci">bool is_open()</div><div class="ttdoc">Return true if a PPM file is currently open. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00159">Utils.h:159</a></div></div>
<div class="ttc" id="neon__convolution_8cpp_xhtml_a565013cf7e49a591bacd548571951f94"><div class="ttname"><a href="neon__convolution_8cpp.xhtml#a565013cf7e49a591bacd548571951f94">gaussian5x5</a></div><div class="ttdeci">const int16_t gaussian5x5[]</div><div class="ttdoc">Gaussian 5x5 matrix. </div><div class="ttdef"><b>Definition:</b> <a href="neon__convolution_8cpp_source.xhtml#l00043">neon_convolution.cpp:43</a></div></div>
-<div class="ttc" id="struct_image_xhtml"><div class="ttname"><a href="struct_image.xhtml">Image</a></div><div class="ttdoc">Structure to hold Image information. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00095">helpers.h:95</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_n_e_convolution3x3_xhtml_a58d050865536a28b56a92eeaf3ac478e"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">arm_compute::NEConvolution3x3::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function&#39;s source, destination, conv and border_mode. </div></div>
+<div class="ttc" id="struct_image_xhtml"><div class="ttname"><a href="struct_image.xhtml">Image</a></div><div class="ttdoc">Structure to hold Image information. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00131">helpers.h:131</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_n_e_convolution3x3_xhtml_a58d050865536a28b56a92eeaf3ac478e"><div class="ttname"><a href="classarm__compute_1_1_n_e_convolution3x3.xhtml#a58d050865536a28b56a92eeaf3ac478e">arm_compute::NEConvolution3x3::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialize the function's source, destination, conv and border_mode. </div></div>
<div class="ttc" id="classarm__compute_1_1_i_n_e_simple_function_xhtml_ab5fd6e96c07aaaed2747c7e16ed5951e"><div class="ttname"><a href="classarm__compute_1_1_i_n_e_simple_function.xhtml#ab5fd6e96c07aaaed2747c7e16ed5951e">arm_compute::INESimpleFunction::run</a></div><div class="ttdeci">void run() overridefinal</div><div class="ttdoc">Run the kernels contained in the function. </div></div>
-<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor&#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00042">TensorInfo.h:42</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00042">TensorInfo.h:42</a></div></div>
<div class="ttc" id="neon__convolution_8cpp_xhtml_a741ba5321da40184f8653e0a50ace070"><div class="ttname"><a href="neon__convolution_8cpp.xhtml#a741ba5321da40184f8653e0a50ace070">gaussian3x3</a></div><div class="ttdeci">const int16_t gaussian3x3[]</div><div class="ttdoc">Gaussian 3x3 matrix. </div><div class="ttdef"><b>Definition:</b> <a href="neon__convolution_8cpp_source.xhtml#l00034">neon_convolution.cpp:34</a></div></div>
-<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a69f2a0e263d4f77d1e166de9cd2746f7"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a69f2a0e263d4f77d1e166de9cd2746f7">arm_compute::utils::PPMLoader::init_image</a></div><div class="ttdeci">void init_image(T &image, arm_compute::Format format)</div><div class="ttdoc">Initialise an image&#39;s metadata with the dimensions of the PPM file currently open. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00125">Utils.h:125</a></div></div>
-<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml">arm_compute::utils::PPMLoader</a></div><div class="ttdoc">Class to load the content of a PPM file into an Image. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00083">Utils.h:83</a></div></div>
+<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a69f2a0e263d4f77d1e166de9cd2746f7"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a69f2a0e263d4f77d1e166de9cd2746f7">arm_compute::utils::PPMLoader::init_image</a></div><div class="ttdeci">void init_image(T &image, arm_compute::Format format)</div><div class="ttdoc">Initialise an image's metadata with the dimensions of the PPM file currently open. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00170">Utils.h:170</a></div></div>
+<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml">arm_compute::utils::PPMLoader</a></div><div class="ttdoc">Class to load the content of a PPM file into an Image. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00128">Utils.h:128</a></div></div>
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+<b>Initial value:</b><div class="fragment"><div class="line">=</div>
+<div class="line">{</div>
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+<div class="line"> 2, 4, 2,</div>
+<div class="line"> 1, 2, 1</div>
+<div class="line">}</div>
+</div><!-- fragment -->
<p>Gaussian 3x3 matrix. </p>
<p>Definition at line <a class="el" href="neon__convolution_8cpp_source.xhtml#l00034">34</a> of file <a class="el" href="neon__convolution_8cpp_source.xhtml">neon_convolution.cpp</a>.</p>
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+<b>Initial value:</b><div class="fragment"><div class="line">=</div>
+<div class="line">{</div>
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+<div class="line"> 6, 24, 36, 24, 6,</div>
+<div class="line"> 4, 16, 24, 16, 4,</div>
+<div class="line"> 1, 4, 6, 4, 1</div>
+<div class="line">}</div>
+</div><!-- fragment -->
<p>Gaussian 5x5 matrix. </p>
<p>Definition at line <a class="el" href="neon__convolution_8cpp_source.xhtml#l00043">43</a> of file <a class="el" href="neon__convolution_8cpp_source.xhtml">neon_convolution.cpp</a>.</p>
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- <li class="navelem"><a class="el" href="dir_d28a4824dc47e487b107a5db32ef43c4.xhtml">examples</a></li><li class="navelem"><a class="el" href="neon__convolution_8cpp.xhtml">neon_convolution.cpp</a></li>
- <li class="footer">Generated on Fri Jun 23 2017 15:44:34 for Compute Library by
+ <li class="navelem"><a class="el" href="dir_1253bad92dedae5edd993ead924afb7b.xhtml">examples</a></li><li class="navelem"><a class="el" href="neon__convolution_8cpp.xhtml">neon_convolution.cpp</a></li>
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- <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
+ <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 </li>
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